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To start understanding better what causes the epidemic in different settings, for the first time, the Global TB Report 2017 presents information from a new multisectoral monitoring framework that identifies linkages with the TB epidemic across seven Sustainable Development Goals (SDGs).
At planning stage, our framework identifies linkages and relevant stakeholders for enabling ATM and therefore allows exploration of context for scaling up.
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Initial analysis involved evaluating linkage groups using the program QuadMap (Durrant et al. 2006), which identifies linkage groups in lines with heterozygous translocations.
Linkage analysis not only identifies linkage regions but allows post hoc analysis of the best inferred haplotypes, generated by programs such as MERLIN.
Estimation of distribution algorithms (EDAs) identify linkages among genes and build models which decompose a given problem.
The aim of this paper is to identify linkages and factors that may simultaneously contribute to these problems.
Thus, this first widespread empirical investigation of AMHG leads us to conclude that AMHG is indeed a widely prevalent natural fluvial phenomenon, and we have identified linkages between known fluvial parameters and AMHG.
Another integral part of recovery will be identifying linkages between isolated populations to ensure healthy genetic exchange and interbreeding.
We first present the approach developed by Dotan-Cohen et al. to identify linkages between biological processes [8].
We used the IPA tool to identify linkages between putative targets of de-regulated miRNAs and differentially expressed genes in mouse scrapie [44], [45].
Bayesian network analysis was then employed to identify linkages between TFs that regulated this hierarchical phase.
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